Big Data Integration Research Center

With the widespread use of the IoT, it is expected that advanced services for a smart and sustainable society will be created by interconnecting a wide variety of sensing data to generate and utilize actionable data that is useful for understanding complex situations in the real world and supporting actions appropriate to the situation. At the Big Data Integration Research Center, we are conducting the research and development of machine learning and data mining technologies for cross-data analysis that appropriately collects sensing data of various types and fields, and discovers, learns, and predicts their cross-sectional associations. We are also working on the research and development of federated AI technology that enables the cross-data analysis model to be adapted to the individually collected data, while at the same time allowing them to be interconnected for overall optimization. The federated AI technology will enable us to perform cross-data analysis using private data in addition to conventional public data so that we can effectively deploy the analysis model to solve various issues. Based on these technologies, we are building a platform necessary for the development of smart services that support safe and comfortable transportation and healthy lifestyles taking into account local environmental issues. We provide APIs for data collaboration and analysis and a user development environment and promote co-creation-based problem solving using users' data and know-how.